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This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process. This tool has some functions such as 2-D visual arrangement of a data set and constraint assignment by mouse manipulation. Moreover, it can execute distance metric learning and k-medoids clustering. In this paper, we show the overview...
Current web is known as a space with constantly growing interactivity among its users. It is changing from the data storage into a social interaction place where people not only search interesting information, but also communicate and collaborate. Obviously, social networks are the most used places for common interaction among people. We present a method for analysis of the strength of relationships...
This paper investigates the behavior of users judging the similarity of documents from the viewpoint of user feedback cost, in particular judgment time and accuracy. An experiment is conducted, in which 21 test participants were asked to judge the similarity of documents. As the clue for the judgment, 3 types of information: original text, snippet, and term, are mutually provided. The judgment accuracy...
We analyze email communications within a large company to reveal how email activity patterns depend on content. We characterize email contents using keywords and examine statistics of email transmissions. As a result, we are able to identify differences in network structures and propagation behaviors depending on the type of keyword.
The Distributed Agents For Autonomy (DAFA) study has been performed for ESA/ESTEC by SciSys UK Ltd, VEGA, and Politecnico di Milano in 2008-2009. The aim of DAFA study has been to examine the application of distributed agent technology to increase the overall performance of a space mission. It is important to note that the distribution should be seen on a system level, including both earth- and space-based...
Since several years, great distribution firms implement more and more complex layout and shelf allocation strategies, so as to force empirical know-how to combine with Artificial Intelligence tools. Thus simulation has become an essential tool for designing efficient article layouts. Mathematical models based on statistical observations have been replaced by agent-based models. In this paper we argue...
In this paper, we propose the use of an agent-based architecture to enhance workflow system capacity to support interprofessional, patient-centred palliative care delivery. This paper outlines the concept of palliative care and describes how agents can be used to assist care providers to address the needs of the patient and family. Our architecture is illustrated in a diagram and the agents are described...
This work presents an unsupervised snippet-based sentiment classification method for Chinese unknown sentiment phrases, which is also applicable to other languages theoretically. Unlike existing Semantic Orientation (SO) methods, our proposed method does not require any Reference Word Pairs (RWPs) for predicting the sentiments of phrases. The results of preliminary experiments show that our proposed...
Research on opinion detection has shown that a large number of opinion-labeled data are necessary for capturing subtle opinions. However, opinion-labeled data, especially at the sub-document level, are often limited. This paper describes the application of Semi-Supervised Learning (SSL) to automatically produce more labeled data and explores the potential of SSL to improve transfer of labeled data...
The k-means method is a widely used clustering technique because of its simplicity and speed. However, the clustering result depends heavily on the chosen initial value. In this report, we propose a seeding method with independent component analysis for the k-means method. Using a benchmark dataset, we evaluate the performance of our proposed method and compare it with other seeding methods.
LBD tools enable the establishment of relationships between concepts appearing in scientific articles in the biomedical field and the generation of new hypotheses via the examination of these existing relationships. In this paper, we study the effectiveness of generally accepted grouping and eliminating logics used in LBD tools. This work is performed in the context of Lit2Info, a system that we have...
Music and singers are influential in local society. An in-depth study on singers is beneficial to various sectors. However, the evolutional characteristic and the daunting complexity of the interrelationship among singers made the problem technically intriguing. In this paper, we present a novel commentary-based social network analysis (CBSNA) methodology to analyze the singer relationships. Developing...
Economic models are found efficient in managing heterogeneous computer resources such as storage, CPU and memory for grid computing. Commodity market, double auction and contract-net-protocol economic models have been widely discussed in the literature. These models are suitable for sharing distributed computer resources that belong to different owners. Agent technology can be used to manage these...
Although static ranked lists remain the dominant Web search interface, they can limit the ability of Web searchers to find desired information when it is buried deep in the collection of search results. Web search visualization and Web search personalization are two active research directions that have shown promise for improving the user experience while searching the Web. In this paper, we propose...
In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper, we demonstrate how social media content can be used to predict real-world outcomes. In particular, we use the chatter from Twitter.com to forecast box-office revenues for movies. We show that...
Opinion mining is of great significance in the analysis of user generated content. While there is some progress in supervised classification of opinion, the unsupervised learning of product features has drawn less attention. Unlike previous approaches based on basic syntactic pattern, our product feature mining utilizes syntactic dependency knowledge in a novel way by discriminating nominal and non-nominal...
In W3C's Rule Interchange Format (RIF), F-Logic rules have received considerable attention as a major logical rule formalism, while combinations of rules with Description Logic (DL) ontologies in RIF, let alone with F-Logic rules, are far less developed. To mend this, we first present F-Logic# knowledge bases, a framework based on the semantics of the well-investigated dl-programs, that provides a...
In this paper, we present a Hierarchical Fuzzy Clustering algorithm which uses domain knowledge to automatically determine the number of clusters and their initial values. The algorithm is applied on a collection of web pages and the results are compared with existing algorithms in the literature.
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